Overview

Dataset statistics

Number of variables19
Number of observations1419
Missing cells11347
Missing cells (%)42.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory201.1 KiB
Average record size in memory145.1 B

Variable types

NUM17
CAT1
BOOL1

Warnings

country has a high cardinality: 152 distinct values High cardinality
producerprice_pigs_carcass_lcupertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_chickens_carcass_lcupertonne is highly correlated with producerprice_pigs_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_chickens_live_lcupertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_pigs_live_lcupertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 5 other fieldsHigh correlation
producerprice_chickens_carcass_slcpertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_pigs_carcass_slcpertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_chickens_live_slcpertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 5 other fieldsHigh correlation
producerprice_pigs_live_slcpertonne is highly correlated with producerprice_chickens_carcass_lcupertonne and 6 other fieldsHigh correlation
producerprice_chickens_carcass_index has 141 (9.9%) missing values Missing
producerprice_pigs_carcass_index has 249 (17.5%) missing values Missing
producerprice_chickens_live_index has 108 (7.6%) missing values Missing
producerprice_pigs_live_index has 231 (16.3%) missing values Missing
producerprice_chickens_carcass_lcupertonne has 996 (70.2%) missing values Missing
producerprice_pigs_carcass_lcupertonne has 1012 (71.3%) missing values Missing
producerprice_chickens_live_lcupertonne has 751 (52.9%) missing values Missing
producerprice_pigs_live_lcupertonne has 774 (54.5%) missing values Missing
producerprice_chickens_carcass_slcpertonne has 996 (70.2%) missing values Missing
producerprice_pigs_carcass_slcpertonne has 1012 (71.3%) missing values Missing
producerprice_chickens_live_slcpertonne has 751 (52.9%) missing values Missing
producerprice_pigs_live_slcpertonne has 774 (54.5%) missing values Missing
producerprice_chickens_carcass_usdpertonne has 1001 (70.5%) missing values Missing
producerprice_pigs_carcass_usdpertonne has 1012 (71.3%) missing values Missing
producerprice_chickens_live_usdpertonne has 758 (53.4%) missing values Missing
producerprice_pigs_live_usdpertonne has 781 (55.0%) missing values Missing
country is uniformly distributed Uniform

Reproduction

Analysis started2022-04-08 16:36:46.739750
Analysis finished2022-04-08 16:37:42.626967
Duration55.89 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

country
Categorical

HIGH CARDINALITY
UNIFORM

Distinct152
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size11.1 KiB
Poland
 
10
Panama
 
10
Qatar
 
10
Palestine
 
10
South Africa
 
10
Other values (147)
1369 
ValueCountFrequency (%) 
Poland100.7%
 
Panama100.7%
 
Qatar100.7%
 
Palestine100.7%
 
South Africa100.7%
 
Belarus100.7%
 
Serbia100.7%
 
Sri Lanka100.7%
 
Czechia100.7%
 
Georgia100.7%
 
Other values (142)131993.0%
 
2022-04-08T09:37:42.742831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2022-04-08T09:37:42.927770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length52
Median length8
Mean length9.665961945
Min length4

year
Real number (ℝ≥0)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.249471
Minimum2011
Maximum2020
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:43.075006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013
median2015
Q32018
95-th percentile2019
Maximum2020
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.732514239
Coefficient of variation (CV)0.001355918598
Kurtosis-1.183578513
Mean2015.249471
Median Absolute Deviation (MAD)2
Skewness0.02173714889
Sum2859639
Variance7.466634065
MonotocityNot monotonic
2022-04-08T09:37:43.190865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
201515110.6%
 
201615110.6%
 
201715110.6%
 
201815110.6%
 
201915110.6%
 
201415010.6%
 
201114910.5%
 
201214910.5%
 
201314910.5%
 
2020674.7%
 
ValueCountFrequency (%) 
201114910.5%
 
201214910.5%
 
201314910.5%
 
201415010.6%
 
201515110.6%
 
ValueCountFrequency (%) 
2020674.7%
 
201915110.6%
 
201815110.6%
 
201715110.6%
 
201615110.6%
 

producerprice_chickens_carcass_index
Real number (ℝ≥0)

MISSING

Distinct124
Distinct (%)9.7%
Missing141
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean100.7597809
Minimum17
Maximum372
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:43.360107image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile73
Q193
median100
Q3107
95-th percentile130
Maximum372
Range355
Interquartile range (IQR)14

Descriptive statistics

Standard deviation20.6932561
Coefficient of variation (CV)0.2053721823
Kurtosis28.46707285
Mean100.7597809
Median Absolute Deviation (MAD)7
Skewness2.698979119
Sum128771
Variance428.2108479
MonotocityNot monotonic
2022-04-08T09:37:43.544818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
100795.6%
 
99634.4%
 
98584.1%
 
101574.0%
 
96493.5%
 
102463.2%
 
94453.2%
 
97443.1%
 
104433.0%
 
95412.9%
 
Other values (114)75353.1%
 
(Missing)1419.9%
 
ValueCountFrequency (%) 
1710.1%
 
2910.1%
 
3210.1%
 
3520.1%
 
3610.1%
 
ValueCountFrequency (%) 
37210.1%
 
23110.1%
 
22710.1%
 
20620.1%
 
19510.1%
 

producerprice_pigs_carcass_index
Real number (ℝ≥0)

MISSING

Distinct114
Distinct (%)9.7%
Missing249
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean102.4495726
Minimum29
Maximum370
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:43.745410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile75
Q193
median100
Q3109
95-th percentile131.55
Maximum370
Range341
Interquartile range (IQR)16

Descriptive statistics

Standard deviation23.04741876
Coefficient of variation (CV)0.2249635422
Kurtosis47.29591154
Mean102.4495726
Median Absolute Deviation (MAD)8
Skewness4.778464402
Sum119866
Variance531.1835114
MonotocityNot monotonic
2022-04-08T09:37:43.892624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
100594.2%
 
99473.3%
 
98473.3%
 
101433.0%
 
95412.9%
 
94412.9%
 
96372.6%
 
106372.6%
 
108362.5%
 
104362.5%
 
Other values (104)74652.6%
 
(Missing)24917.5%
 
ValueCountFrequency (%) 
2910.1%
 
3110.1%
 
3210.1%
 
3620.1%
 
4810.1%
 
ValueCountFrequency (%) 
37010.1%
 
36010.1%
 
34510.1%
 
32710.1%
 
19510.1%
 

producerprice_chickens_live_index
Real number (ℝ≥0)

MISSING

Distinct128
Distinct (%)9.8%
Missing108
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean100.5560641
Minimum31
Maximum440
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:44.077539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile73
Q194
median100
Q3106
95-th percentile127
Maximum440
Range409
Interquartile range (IQR)12

Descriptive statistics

Standard deviation21.11881382
Coefficient of variation (CV)0.2100202908
Kurtosis64.5269335
Mean100.5560641
Median Absolute Deviation (MAD)6
Skewness4.789285751
Sum131829
Variance446.0042972
MonotocityNot monotonic
2022-04-08T09:37:44.246943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
100886.2%
 
98725.1%
 
101674.7%
 
99614.3%
 
96563.9%
 
97523.7%
 
105483.4%
 
104453.2%
 
95412.9%
 
94412.9%
 
Other values (118)74052.1%
 
(Missing)1087.6%
 
ValueCountFrequency (%) 
3110.1%
 
3220.1%
 
3410.1%
 
3510.1%
 
3820.1%
 
ValueCountFrequency (%) 
44010.1%
 
31810.1%
 
26810.1%
 
23510.1%
 
19610.1%
 

producerprice_pigs_live_index
Real number (ℝ≥0)

MISSING

Distinct124
Distinct (%)10.4%
Missing231
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean102.8282828
Minimum10
Maximum522
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:44.431869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile74
Q193
median100
Q3108
95-th percentile129
Maximum522
Range512
Interquartile range (IQR)15

Descriptive statistics

Standard deviation27.30323602
Coefficient of variation (CV)0.2655226293
Kurtosis64.24668558
Mean102.8282828
Median Absolute Deviation (MAD)8
Skewness5.608565787
Sum122160
Variance745.4666973
MonotocityNot monotonic
2022-04-08T09:37:44.594607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
100704.9%
 
101463.2%
 
99463.2%
 
105453.2%
 
98453.2%
 
97433.0%
 
94372.6%
 
96362.5%
 
102362.5%
 
104342.4%
 
Other values (114)75052.9%
 
(Missing)23116.3%
 
ValueCountFrequency (%) 
1010.1%
 
1720.1%
 
2720.1%
 
3510.1%
 
3620.1%
 
ValueCountFrequency (%) 
52210.1%
 
35610.1%
 
31010.1%
 
30610.1%
 
29810.1%
 

producerprice_chickens_carcass_lcupertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct398
Distinct (%)94.1%
Missing996
Missing (%)70.2%
Infinite0
Infinite (%)0.0%
Mean2887876.288
Minimum1032
Maximum98955653
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:44.779676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1032
5-th percentile1318.1
Q14028.5
median17698
Q3250449
95-th percentile5129833.1
Maximum98955653
Range98954621
Interquartile range (IQR)246420.5

Descriptive statistics

Standard deviation13863304.8
Coefficient of variation (CV)4.800518934
Kurtosis35.27458702
Mean2887876.288
Median Absolute Deviation (MAD)16019
Skewness5.941415946
Sum1221571670
Variance1.9219122e+14
MonotocityNot monotonic
2022-04-08T09:37:44.964483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
600050.4%
 
1267740.3%
 
1166030.2%
 
211320.1%
 
250000020.1%
 
131320.1%
 
151020.1%
 
1541920.1%
 
71050220.1%
 
43613720.1%
 
Other values (388)39728.0%
 
(Missing)99670.2%
 
ValueCountFrequency (%) 
103210.1%
 
105210.1%
 
110710.1%
 
112210.1%
 
115010.1%
 
ValueCountFrequency (%) 
9895565310.1%
 
9651230910.1%
 
9576000010.1%
 
9452800010.1%
 
9444500010.1%
 

producerprice_pigs_carcass_lcupertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct377
Distinct (%)92.6%
Missing1012
Missing (%)71.3%
Infinite0
Infinite (%)0.0%
Mean2030616.16
Minimum1139
Maximum46711000
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:45.194683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1139
5-th percentile1404.6
Q12074.5
median17621
Q3183015
95-th percentile8048333.3
Maximum46711000
Range46709861
Interquartile range (IQR)180940.5

Descriptive statistics

Standard deviation7894335.045
Coefficient of variation (CV)3.88765499
Kurtosis21.40139092
Mean2030616.16
Median Absolute Deviation (MAD)16121
Skewness4.687553628
Sum826460777
Variance6.23205258e+13
MonotocityNot monotonic
2022-04-08T09:37:45.365571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1762140.3%
 
648040.3%
 
1763730.2%
 
43540030.2%
 
275000030.2%
 
152030.2%
 
47603020.1%
 
450020.1%
 
950020.1%
 
158420.1%
 
Other values (367)37926.7%
 
(Missing)101271.3%
 
ValueCountFrequency (%) 
113910.1%
 
114010.1%
 
114410.1%
 
123210.1%
 
124510.1%
 
ValueCountFrequency (%) 
4671100010.1%
 
4639000010.1%
 
4626300010.1%
 
4617000010.1%
 
4607563410.1%
 

producerprice_chickens_live_lcupertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct617
Distinct (%)92.4%
Missing751
Missing (%)52.9%
Infinite0
Infinite (%)0.0%
Mean1201356.41
Minimum478
Maximum42588000
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:45.543846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum478
5-th percentile860.7
Q11857
median8159
Q394078.75
95-th percentile2971781.95
Maximum42588000
Range42587522
Interquartile range (IQR)92221.75

Descriptive statistics

Standard deviation5244542.578
Coefficient of variation (CV)4.365517621
Kurtosis28.435659
Mean1201356.41
Median Absolute Deviation (MAD)7227
Skewness5.311953918
Sum802506082
Variance2.750522685e+13
MonotocityNot monotonic
2022-04-08T09:37:45.713133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
160070.5%
 
107760.4%
 
903960.4%
 
333340.3%
 
350030.2%
 
506030.2%
 
191176530.2%
 
400030.2%
 
93220.1%
 
131020.1%
 
Other values (607)62944.3%
 
(Missing)75152.9%
 
ValueCountFrequency (%) 
47810.1%
 
52610.1%
 
53510.1%
 
54110.1%
 
77210.1%
 
ValueCountFrequency (%) 
4258800010.1%
 
3778000010.1%
 
3586933310.1%
 
3451200010.1%
 
3356533310.1%
 

producerprice_pigs_live_lcupertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct605
Distinct (%)93.8%
Missing774
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean986008.5767
Minimum829
Maximum34651034
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:45.898075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum829
5-th percentile1104.6
Q12584
median14677
Q3133021
95-th percentile3536830.6
Maximum34651034
Range34650205
Interquartile range (IQR)130437

Descriptive statistics

Standard deviation4370967.167
Coefficient of variation (CV)4.432991021
Kurtosis34.25450521
Mean986008.5767
Median Absolute Deviation (MAD)13465
Skewness5.819191122
Sum635975532
Variance1.910535398e+13
MonotocityNot monotonic
2022-04-08T09:37:46.067395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
13228120.8%
 
680170.5%
 
504040.3%
 
1100040.3%
 
2175330.2%
 
192857130.2%
 
121230.2%
 
116220.1%
 
641820.1%
 
103420.1%
 
Other values (595)60342.5%
 
(Missing)77454.5%
 
ValueCountFrequency (%) 
82910.1%
 
89310.1%
 
91210.1%
 
93610.1%
 
95710.1%
 
ValueCountFrequency (%) 
3465103410.1%
 
3268891610.1%
 
3152979310.1%
 
3075738620.1%
 
3010000010.1%
 

producerprice_chickens_carcass_slcpertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct397
Distinct (%)93.9%
Missing996
Missing (%)70.2%
Infinite0
Infinite (%)0.0%
Mean2809386.832
Minimum1032
Maximum98955653
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:46.261456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1032
5-th percentile1318.1
Q12838
median17042
Q3249500
95-th percentile4987058.4
Maximum98955653
Range98954621
Interquartile range (IQR)246662

Descriptive statistics

Standard deviation13832228.72
Coefficient of variation (CV)4.923575693
Kurtosis35.75221365
Mean2809386.832
Median Absolute Deviation (MAD)15363
Skewness5.993882377
Sum1188370630
Variance1.913305513e+14
MonotocityNot monotonic
2022-04-08T09:37:46.430829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
600050.4%
 
1267740.3%
 
1166030.2%
 
25000020.1%
 
250000020.1%
 
131320.1%
 
2000020.1%
 
933820.1%
 
251820.1%
 
151020.1%
 
Other values (387)39728.0%
 
(Missing)99670.2%
 
ValueCountFrequency (%) 
103210.1%
 
105210.1%
 
110710.1%
 
112210.1%
 
115010.1%
 
ValueCountFrequency (%) 
9895565310.1%
 
9651230910.1%
 
9576000010.1%
 
9452800010.1%
 
9444500010.1%
 

producerprice_pigs_carcass_slcpertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct377
Distinct (%)92.6%
Missing1012
Missing (%)71.3%
Infinite0
Infinite (%)0.0%
Mean1907944.464
Minimum1139
Maximum46711000
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:46.631420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1139
5-th percentile1404.6
Q12074.5
median17621
Q3176108.5
95-th percentile6479928.8
Maximum46711000
Range46709861
Interquartile range (IQR)174034

Descriptive statistics

Standard deviation7728339.622
Coefficient of variation (CV)4.050610365
Kurtosis23.49112978
Mean1907944.464
Median Absolute Deviation (MAD)16113
Skewness4.913892725
Sum776533397
Variance5.972723332e+13
MonotocityNot monotonic
2022-04-08T09:37:47.117422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1762140.3%
 
648040.3%
 
1763730.2%
 
275000030.2%
 
152030.2%
 
43540030.2%
 
260020.1%
 
950020.1%
 
1543220.1%
 
158420.1%
 
Other values (367)37926.7%
 
(Missing)101271.3%
 
ValueCountFrequency (%) 
113910.1%
 
114010.1%
 
114410.1%
 
123210.1%
 
124510.1%
 
ValueCountFrequency (%) 
4671100010.1%
 
4639000010.1%
 
4626300010.1%
 
4617000010.1%
 
4607563410.1%
 

producerprice_chickens_live_slcpertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct612
Distinct (%)91.6%
Missing751
Missing (%)52.9%
Infinite0
Infinite (%)0.0%
Mean1096886.933
Minimum478
Maximum42588000
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:47.302436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum478
5-th percentile862.7
Q11722.25
median7523.5
Q387906.25
95-th percentile2800130.05
Maximum42588000
Range42587522
Interquartile range (IQR)86184

Descriptive statistics

Standard deviation5141798.49
Coefficient of variation (CV)4.687628539
Kurtosis31.25289844
Mean1096886.933
Median Absolute Deviation (MAD)6587.5
Skewness5.603310482
Sum732720471
Variance2.643809171e+13
MonotocityNot monotonic
2022-04-08T09:37:47.534050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
160070.5%
 
107760.4%
 
903960.4%
 
333340.3%
 
400030.2%
 
92630.2%
 
91330.2%
 
350030.2%
 
191176530.2%
 
506030.2%
 
Other values (602)62744.2%
 
(Missing)75152.9%
 
ValueCountFrequency (%) 
47810.1%
 
52610.1%
 
53510.1%
 
54110.1%
 
55610.1%
 
ValueCountFrequency (%) 
4258800010.1%
 
3778000010.1%
 
3586933310.1%
 
3451200010.1%
 
3356533310.1%
 

producerprice_pigs_live_slcpertonne
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct602
Distinct (%)93.3%
Missing774
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean812515.093
Minimum829
Maximum34651034
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:47.703354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum829
5-th percentile1121
Q12356
median13228
Q3126383
95-th percentile2206696.4
Maximum34651034
Range34650205
Interquartile range (IQR)124027

Descriptive statistics

Standard deviation3989071.658
Coefficient of variation (CV)4.909535456
Kurtosis46.52855086
Mean812515.093
Median Absolute Deviation (MAD)12048
Skewness6.770194231
Sum524072235
Variance1.591269269e+13
MonotocityNot monotonic
2022-04-08T09:37:47.919630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
13228120.8%
 
680170.5%
 
504040.3%
 
1100040.3%
 
248640.3%
 
121230.2%
 
192857130.2%
 
116220.1%
 
255820.1%
 
142420.1%
 
Other values (592)60242.4%
 
(Missing)77454.5%
 
ValueCountFrequency (%) 
82910.1%
 
93610.1%
 
95710.1%
 
98710.1%
 
101310.1%
 
ValueCountFrequency (%) 
3465103410.1%
 
3268891610.1%
 
3152979310.1%
 
3075738620.1%
 
3010000010.1%
 

producerprice_chickens_carcass_usdpertonne
Real number (ℝ≥0)

MISSING

Distinct387
Distinct (%)92.6%
Missing1001
Missing (%)70.5%
Infinite0
Infinite (%)0.0%
Mean2834.574163
Minimum950
Maximum7794
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:48.104594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum950
5-th percentile1316.65
Q11857.5
median2472
Q33502.25
95-th percentile5367.95
Maximum7794
Range6844
Interquartile range (IQR)1644.75

Descriptive statistics

Standard deviation1280.544839
Coefficient of variation (CV)0.4517591587
Kurtosis0.5154892801
Mean2834.574163
Median Absolute Deviation (MAD)767
Skewness0.9681768281
Sum1184852
Variance1639795.084
MonotocityNot monotonic
2022-04-08T09:37:48.273919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
469540.3%
 
206830.2%
 
431930.2%
 
286030.2%
 
184730.2%
 
346620.1%
 
425920.1%
 
201120.1%
 
462120.1%
 
134220.1%
 
Other values (377)39227.6%
 
(Missing)100170.5%
 
ValueCountFrequency (%) 
95010.1%
 
96810.1%
 
102810.1%
 
103910.1%
 
107510.1%
 
ValueCountFrequency (%) 
779410.1%
 
720410.1%
 
716910.1%
 
642410.1%
 
632210.1%
 

producerprice_pigs_carcass_usdpertonne
Real number (ℝ≥0)

MISSING

Distinct381
Distinct (%)93.6%
Missing1012
Missing (%)71.3%
Infinite0
Infinite (%)0.0%
Mean2822.614251
Minimum1236
Maximum6957
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:48.452392image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1236
5-th percentile1534.6
Q11982.5
median2454
Q33280.5
95-th percentile5673.2
Maximum6957
Range5721
Interquartile range (IQR)1298

Descriptive statistics

Standard deviation1226.677467
Coefficient of variation (CV)0.4345891283
Kurtosis1.438180284
Mean2822.614251
Median Absolute Deviation (MAD)579
Skewness1.408815714
Sum1148804
Variance1504737.607
MonotocityNot monotonic
2022-04-08T09:37:48.621716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
254440.3%
 
652640.3%
 
316030.2%
 
653230.2%
 
183520.1%
 
195220.1%
 
166920.1%
 
309120.1%
 
170720.1%
 
278520.1%
 
Other values (371)38126.8%
 
(Missing)101271.3%
 
ValueCountFrequency (%) 
123610.1%
 
126110.1%
 
126310.1%
 
133610.1%
 
135110.1%
 
ValueCountFrequency (%) 
695710.1%
 
684010.1%
 
653230.2%
 
652640.3%
 
646110.1%
 

producerprice_chickens_live_usdpertonne
Real number (ℝ≥0)

MISSING

Distinct585
Distinct (%)88.5%
Missing758
Missing (%)53.4%
Infinite0
Infinite (%)0.0%
Mean1923.576399
Minimum445
Maximum7859
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:48.822323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum445
5-th percentile888
Q11166
median1517
Q32330
95-th percentile4387
Maximum7859
Range7414
Interquartile range (IQR)1164

Descriptive statistics

Standard deviation1172.68468
Coefficient of variation (CV)0.609637694
Kurtosis4.201603597
Mean1923.576399
Median Absolute Deviation (MAD)469
Skewness1.910726961
Sum1271484
Variance1375189.36
MonotocityNot monotonic
2022-04-08T09:37:48.975993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
334860.4%
 
118740.3%
 
96430.2%
 
119430.2%
 
187430.2%
 
156830.2%
 
131330.2%
 
400030.2%
 
120530.2%
 
93030.2%
 
Other values (575)62744.2%
 
(Missing)75853.4%
 
ValueCountFrequency (%) 
44510.1%
 
54710.1%
 
54910.1%
 
55010.1%
 
61910.1%
 
ValueCountFrequency (%) 
785910.1%
 
735310.1%
 
698710.1%
 
692910.1%
 
678310.1%
 

producerprice_pigs_live_usdpertonne
Real number (ℝ≥0)

MISSING

Distinct543
Distinct (%)85.1%
Missing781
Missing (%)55.0%
Infinite0
Infinite (%)0.0%
Mean2060.556426
Minimum414
Maximum7174
Zeros0
Zeros (%)0.0%
Memory size11.1 KiB
2022-04-08T09:37:49.170046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum414
5-th percentile960.9
Q11382
median1732.5
Q32448.75
95-th percentile4532.85
Maximum7174
Range6760
Interquartile range (IQR)1066.75

Descriptive statistics

Standard deviation1053.694257
Coefficient of variation (CV)0.5113639422
Kurtosis3.413012177
Mean2060.556426
Median Absolute Deviation (MAD)462.5
Skewness1.691337424
Sum1314635
Variance1110271.588
MonotocityNot monotonic
2022-04-08T09:37:49.323744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
4899120.8%
 
248640.3%
 
136140.3%
 
407440.3%
 
136330.2%
 
114330.2%
 
184930.2%
 
172130.2%
 
164920.1%
 
182320.1%
 
Other values (533)59842.1%
 
(Missing)78155.0%
 
ValueCountFrequency (%) 
41410.1%
 
46310.1%
 
47310.1%
 
50710.1%
 
54410.1%
 
ValueCountFrequency (%) 
717410.1%
 
688110.1%
 
680410.1%
 
632210.1%
 
553710.1%
 
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
False
1322 
True
 
97
ValueCountFrequency (%) 
False132293.2%
 
True976.8%
 
2022-04-08T09:37:49.477060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Interactions

2022-04-08T09:36:54.097929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:54.398652image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:54.692078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:54.901324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.105557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.297458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.459416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.611456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.773263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:55.934938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:56.107033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:56.259392image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:56.421087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:56.628061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:56.781708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.013438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.167177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.314290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.483467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.646196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.799861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:57.953442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.126601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.288363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.447874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.621832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.792484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:58.956057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:59.115592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:59.280037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:59.442508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:59.734493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:36:59.897270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.082145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.250751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.382234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.551478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.698585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.836580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:00.983694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.152958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.300062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.438214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.600956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.754584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:01.901731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.039686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.202462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.356091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.503206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.641206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.804074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:02.942064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.089181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.236240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.376724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.525406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.674685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:03.821785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.006374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.226961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.388560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.529705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.690551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.840063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:04.984215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.122252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.253503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.386563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.538806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.701572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:05.839582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:06.171579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:06.340905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:06.525718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:06.657215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:06.826530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.020548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.174179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.305680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.475032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.628731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.775856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:07.923005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.061046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.192571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.361922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.509026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.678157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.847446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:08.994630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.163908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.311013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.480223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.649534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.812286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:09.965996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.135924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.282173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.435876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.614299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.783608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:10.937297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.084527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.215978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.371117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.516770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.654740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.801940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:11.939944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.087138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.218707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.372398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.503883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.641932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.789053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:12.936159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.074184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.205686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.343684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.506583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.660243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:13.992271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:14.145967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:14.324366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:14.559686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:14.721185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:14.897573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.067479image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.229002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.384242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.567687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.714879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:15.884323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.031504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.185271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.348077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.517361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.671119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.833933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:16.972063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.188213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.335369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.489048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.658406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.805640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:17.959333image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.106569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.260278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.423134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.576926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.724108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:18.961941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.109135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.278427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.443085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.626069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.764096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:19.926915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.080592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.243132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.396869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.566155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.728982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:20.898364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.061176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.214924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.384226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.547036image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.716365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:21.863464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.001623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.148762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.286928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.418472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.572163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.719324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:22.850890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.004630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.151837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.289914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.421412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.775220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:23.922414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.069595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.207721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.339328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.477371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.724893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:24.894255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.040909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.210280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.357429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.526831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.680517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.843353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:25.997081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.175439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.329146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.498473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.661278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.830651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:26.984307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.131502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.331960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.485648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.648465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.817831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:27.964939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.118771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.265882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.419596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.566699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.720351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:28.918552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.067733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.221483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.370637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.538006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.691699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.839417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:29.974303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.139168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.292838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.440043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.609304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.756496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:30.910296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.057482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.211142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.358291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.542930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.690086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.843866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:31.997536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.144705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.298357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.445565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.592716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.746512image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:32.893656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.031787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.163347image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.316989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.463809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.617470image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.764544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:33.918326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.065511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.203610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.350802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.504495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.667308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:34.852298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.005969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.137548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.522343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.669537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.807561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:35.985961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.139699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.286896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.409320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.572164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.710215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.857405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:36.988904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.142613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.274174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.458883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.612550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.759741image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:37.891315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.029406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.176636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.308195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.430578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.577764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.715802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:38.879738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.016494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.163740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.295225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.433359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.596052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.734262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:39.865750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:40.012973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:40.135391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2022-04-08T09:37:49.624173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-04-08T09:37:50.047271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-04-08T09:37:50.448118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-04-08T09:37:50.905887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-04-08T09:37:40.420610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:41.022368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:41.601585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2022-04-08T09:37:42.357418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

countryyearproducerprice_chickens_carcass_indexproducerprice_pigs_carcass_indexproducerprice_chickens_live_indexproducerprice_pigs_live_indexproducerprice_chickens_carcass_lcupertonneproducerprice_pigs_carcass_lcupertonneproducerprice_chickens_live_lcupertonneproducerprice_pigs_live_lcupertonneproducerprice_chickens_carcass_slcpertonneproducerprice_pigs_carcass_slcpertonneproducerprice_chickens_live_slcpertonneproducerprice_pigs_live_slcpertonneproducerprice_chickens_carcass_usdpertonneproducerprice_pigs_carcass_usdpertonneproducerprice_chickens_live_usdpertonneproducerprice_pigs_live_usdpertonnecountry_inscope
0Afghanistan2011111.0NaN111.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
1Afghanistan2012113.0NaN113.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
2Afghanistan2013109.0NaN109.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
3Afghanistan2014105.0NaN105.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
4Afghanistan2015101.0NaN101.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
5Afghanistan201693.0NaN93.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
6Afghanistan201790.0NaN90.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
7Afghanistan201885.0NaN85.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
8Afghanistan201988.0NaN88.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
9Albania201169.0109.069.087.0338000.0563000.0NaN297488.0338000.0563000.0NaN297488.03350.05580.0NaN2948.0False

Last rows

countryyearproducerprice_chickens_carcass_indexproducerprice_pigs_carcass_indexproducerprice_chickens_live_indexproducerprice_pigs_live_indexproducerprice_chickens_carcass_lcupertonneproducerprice_pigs_carcass_lcupertonneproducerprice_chickens_live_lcupertonneproducerprice_pigs_live_lcupertonneproducerprice_chickens_carcass_slcpertonneproducerprice_pigs_carcass_slcpertonneproducerprice_chickens_live_slcpertonneproducerprice_pigs_live_slcpertonneproducerprice_chickens_carcass_usdpertonneproducerprice_pigs_carcass_usdpertonneproducerprice_chickens_live_usdpertonneproducerprice_pigs_live_usdpertonnecountry_inscope
1409Zambia2016108.0113.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
1410Zambia201779.082.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
1411Zambia2018139.0124.0NaNNaN27146.042080.0NaNNaN27146.042080.0NaNNaN2596.04024.0NaNNaNFalse
1412Zambia2019151.0131.0NaNNaN29464.044357.0NaNNaN29464.044357.0NaNNaN2286.03441.0NaNNaNFalse
1413Zimbabwe2014NaNNaN105.0NaNNaNNaN4333.0NaNNaNNaN4333.0NaNNaNNaN4333.0NaNFalse
1414Zimbabwe2015NaNNaN97.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNFalse
1415Zimbabwe2016NaNNaN97.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNFalse
1416Zimbabwe2017NaNNaN97.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNNaNNaN4000.0NaNFalse
1417Zimbabwe2018NaNNaN114.0NaNNaNNaN4667.0NaNNaNNaN4667.0NaNNaNNaN4667.0NaNFalse
1418Zimbabwe2019NaNNaN82.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse